Integrating milk metabolite profile information for the prediction of traditional milk traits based on SNP information for Holstein cows.

ABSTRACT: In this study the benefit of metabolome level analysis for the prediction of genetic value of three traditional milk traits was investigated. Our proposed approach consists of three steps: First, milk metabolite profiles are used to predict three traditional milk traits of 1,305 Holstein cows. Two regression methods, both enabling variable selection, are applied to identify important milk metabolites in this step. Second, the prediction of these important milk metabolite from single nucleotide polymorphisms (SNPs) enables the detection of SNPs with significant genetic effects. Finally, these SNPs are used to predict milk traits. The observed precision of predicted genetic values was compared to the results observed for the classical genotype-phenotype prediction using all SNPs or a reduced

SUBMITTER: Melzer N 

PROVIDER: S-EPMC3749218 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature